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Predictive Density Construction and Accuracy Testing with Multiple Possibly Misspecified Diffusion Models

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  • Norman R. Swanson

    ()
    (Rutgers University)

  • Valentina Corradi

    ()
    (University of Warwick)

Abstract

This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, we construct accuracy assessment tests that are in the spirit of Diebold and Mariano (1995) and White (2000). In order to establish the asymptotic properties of our tests, we also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and Salani´e (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.

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Bibliographic Info

Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201112.

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Length: 20 pages
Date of creation: 15 May 2011
Date of revision:
Handle: RePEc:rut:rutres:201112

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Keywords: block bootstrap; diffusion processes; jumps; nonparametric simulated quasi maximum likelihood; parameter estimation error;

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References

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  1. Gourieroux, C. & Monfort, A. & Renault, E., 1992. "Indirect Inference," Papers 92.279, Toulouse - GREMAQ.
  2. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive Density Evaluation," Handbook of Economic Forecasting, Elsevier.
  3. Yacine Ait-Sahalia, 1995. "Testing Continuous-Time Models of the Spot Interest Rate," NBER Working Papers 5346, National Bureau of Economic Research, Inc.
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  6. Corradi, Valentina & Swanson, Norman R., 2005. "A Test For Comparing Multiple Misspecified Conditional Interval Models," Econometric Theory, Cambridge University Press, vol. 21(05), pages 991-1016, October.
  7. Corradi, Valentina & Swanson, Norman R., 2007. "Evaluation of dynamic stochastic general equilibrium models based on distributional comparison of simulated and historical data," Journal of Econometrics, Elsevier, vol. 136(2), pages 699-723, February.
  8. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
  9. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive density and conditional confidence interval accuracy tests," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 187-228.
  10. Chacko, George & Viceira, Luis M., 2003. "Spectral GMM estimation of continuous-time processes," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 259-292.
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  33. Valentina Corradi & Norman Swanson, 2006. "Predictive Density Evaluation. Revised," Departmental Working Papers 200621, Rutgers University, Department of Economics.
  34. Samuel Thompson, 2008. "Identifying Term Structure Volatility from the LIBOR-Swap Curve," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 819-854, April.
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Citations

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Cited by:
  1. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
  2. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.

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